基于高斯-牛顿优化的近线性相位IIR滤波器

Jasper Tan, C. Burrus
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引用次数: 1

摘要

在本文中,我们提出了一种简单的基于优化的方法来设计基于高斯-牛顿方法的近线性相位IIR滤波器,并探讨了它相对于对称FIR滤波器的优点。我们证明了IIR低通滤波器比相应的FIR滤波器具有更低的群延迟、更低的阶数和更低的幅度误差,同时在通带内仍然保持R2≥0.99的相位响应线性度。这种滤波器在近似而不是精确线性相位足够的应用中是有益的。代码可在作者的网站上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Near-Linear-Phase IIR Filters Using Gauss-Newton Optimization
In this paper, we present a simple optimization-based method for designing near-linear-phase IIR filters based on the Gauss-Newton method, and we explore its benefits over symmetric FIR filters. We demonstrate IIR low-pass filters with lower group delay, lower order, and lower magnitude errors than corresponding FIR filters while still maintaining a phase response linearity of R2 ≥ 0.99 in the passband. Such filters can be beneficial in applications where approximate, rather than exact, linear phase is sufficient. Code is available on the author’s website.
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